System and method for determining timing of response in a group communication using artificial intelligence

ABSTRACT

Efficient use of channel bandwidth response, response timing, along with the ability to acquire the most accurate and up to date response are provided for management of virtual assistant search queries within a communication system ( 100 ). Improved management is obtained using an artificial intelligence (AI) server ( 104 ) controlling response activity to a query communication device ( 102 ) by incorporating one or more of: adjusting verbosity of responses ( 158 ), redirecting queries from the AI server to alternate resources ( 412 ), and/or prioritizing of a response ( 506 ) based on wait time.

RELATED APPLICATIONS

This application is related to co-pending application filed as U.S.application Ser. No. 15/390,816 and co-pending application filed as U.S.application Ser. No. 15/390,797 commonly assigned to and owned byMotorola Solutions, Inc.

FIELD OF THE INVENTION

The present invention relates generally to radio communication systemsand more particularly to the application of artificial intelligence inradio communication systems.

BACKGROUND

Being able to get the best search out of every search query through avirtual assistant without impeding communications is important, not onlyto the user of the query device but also within the management of theoverall communication system. A server utilized in virtual assistantqueries and responses may be managing many queries sent from differentdevices at one time. Efficient use of channel bandwidth, responsetiming, along with the ability to acquire the most accurate and up todate response are all important factors of consideration in themanagement of virtual assistant search queries within a communicationsystem offering such searching capability. Systems that have had limitedopportunity to take advantage of virtual assistant searchingcapabilities, such as public safety communication systems, would be ableto consider incorporating such search capabilities if improvements weremade in the ability to manage the system. Such improvements wouldbenefit not only public safety applications, but any communicationsystem incorporating virtual assistant query capability.

Accordingly, there is a need for improving the management of virtualsearching capabilities within a communication system.

BRIEF DESCRIPTION OF THE FIGURES

The accompanying figures, where like reference numerals refer toidentical or functionally similar elements throughout the separateviews, together with the detailed description below, are incorporated inand form part of the specification, and serve to further illustrateembodiments of concepts that include the claimed invention, and explainvarious principles and advantages of those embodiments.

FIG. 1A is a communication system block diagram formed and operating inaccordance with some embodiments.

FIG. 1B is a flowchart for managing verbosity of response in accordancewith some embodiments.

FIG. 2 is a communication system block diagram formed and operating inaccordance with some embodiments.

FIG. 3 is a communication exchange diagram in accordance with someembodiments.

FIG. 4 is a flowchart for obtaining supplemental information inaccordance with some embodiments.

FIG. 5 is a flowchart for a timing method in accordance with someembodiments.

Skilled artisans will appreciate that elements in the figures areillustrated for simplicity and clarity and have not necessarily beendrawn to scale. For example, the dimensions of some of the elements inthe figures may be exaggerated relative to other elements to help toimprove understanding of embodiments of the present invention.

The apparatus and method components have been represented whereappropriate by conventional symbols in the drawings, showing only thosespecific details that are pertinent to understanding the embodiments ofthe present invention so as not to obscure the disclosure with detailsthat will be readily apparent to those of ordinary skill in the arthaving the benefit of the description herein.

DETAILED DESCRIPTION

Briefly, there is provided herein an artificial intelligence serverproviding natural language processing and query response operationincorporated into a communication system. The AI server of the variousembodiments responds to queries from one or more radios within thecommunication system. The various methods utilized by the AI serverwithin the various embodiments serve to minimize disruption incommunication, maximize channel usage, and prioritize responses. The AIserver operating in accordance with one or more of these methods isbeneficial to all types of communication systems, including but notlimited to broadband systems, and even extending into broadbandhalf-duplex enabled systems, and narrowband half-duplex systems, to namea few. The benefits of extending the AI server capabilities intohalf-duplex communication systems, allows public safety radiocommunication system to advantageously provide search query capability,via virtual searching, not readily available to public safety radiousers in the past.

FIG. 1A shows a communication system 100 comprising a wirelesscommunication device 102, an artificial intelligence (AI) server 104,operating within a communications network 106 in accordance with someembodiments. The AI server 104 comprises language processing andresponse capability to operate as a virtual assistant. Virtualassistants, such as Sin provided by Apple, Inc.® and Google Now providedby Google, Inc.®, are software applications that understand naturallanguage and complete electronic tasks in response to user inputs. Thecommunication device 102 may be any broadband or narrowband devicehaving a microprocessor, transceiver, and audio circuitry, such as aradio, a cell phone or the like, for receiving a verbal query user inputfor transmission to the AI server 104.

The AI server 104 controls query and response activity in an optimizedmanner between the AI server 104 and the communication device 102thereby maintaining an efficient use of channel bandwidth. In accordancewith some embodiments, the AI server 104 provides prioritization ofresponses sent from the AI server 104 to the query, based on verbosityof the response and channel availability within the communication system100. The verbose response may be adjusted so as not to exceed availablechannel bandwidth in a variety of ways. For example, the AI server maymanage a verbose response by prioritizing content within the verboseresponse, and then segmenting the prioritized content into shorterprioritized responses, thereby efficiently filling up available channelbandwidth without exceeding the available channel bandwidth. Contentprioritization may further be based on, for example, the length and/orcomplexity of the verbose response. Thus, different priority factors canbe used in segmenting a response.

In accordance with some embodiments, AI server 104 may also adjustverbosity of response by forming condensed responses. Adjustingverbosity through the use of a condensed response can be accomplished inmany ways, for example by using acronyms instead of complete words,using alternative shorter words, removing extraneous words, and usingpredetermined codenames, to name a few. The AI server may also takeprioritized responses described previously and form condensed responses.The completeness of the information in the condensed response can beadjusted based on the channel availability. For example, condensing aresponse by removing less important information from the response orsending less important information at a later time when channelavailability has improved will enhance overall operational efficiency.Hence, by adjusting verbosity of response, the AI server 104 of theembodiments provides for improved operational efficiency ofcommunication system 100.

For additional efficient channel bandwidth management, the AI server 104may further provide interrupt capability for responses containing higherpriority content. Thus, if communication device 102 is in the midst ofplaying out information in response to a query pertaining to somegeneral facet of information, the AI server can interrupt the responsewith a higher priority response.

Referring to FIG. 1B, there is provided a method 150 of varyinginformation for optimized use of channel availability in a communicationsystem in accordance with the some of the embodiments. The method 150begins at 152 by receiving a query at an artificial intelligence (AI)server, such as AI server 104, the AI server having natural languageprocessing and response capability. The query to the AI server may be inthe form of verbal queries or a combination of verbal with text query.

In accordance with the type of query sent, the AI server in this casegenerates a verbose response to the query at 154. Moving to 156, the AIserver determines channel availability for the verbose response, andthen adjusts verbosity of response at 158 based on channel availability,wherein channel availability is based on channel bandwidth and channeloccupancy. The adjusted response to the query is sent at 160. Hence, thecommunication system 100 and method 150 provide an AI server thatdetermines channel availability for a verbose response to acommunication device and manages the verbosity of response acrossavailable channels within the communication system.

In accordance with these method embodiments, the adjusting verbosity ofthe response may be accomplished in several different ways, includingbut not limited to: summarizing content of the response to occupy thechannel bandwidth, and/or condensing content of the response so as notto exceed available channel bandwidth. The adjusting verbosity of theresponse may also be accomplished by prioritizing content of the verboseresponse; and segmenting the prioritized content into shorter segmentedresponses, thereby freeing up the channel bandwidth between responses.

Responses can be interrupted based on priority. For example an adjustedresponse currently being played out at a device can be interrupted byanother response, wherein that other response contains content havinghigher priority content.

Hence, the system 100 and method 150 of the embodiments provide formanagement of a verbose response with which to efficiently use availablechannel bandwidth.

FIG. 2 is a communication system 200 formed and operating in accordancewith some embodiments. Communication system 200 comprises a plurality ofcommunication devices 210, comprising a plurality of half-duplex radioswhich may be portable handheld operated radios or mobile vehicularradios. These half-duplex radios communicate (transmit mode) using apush-to-talk (PTT) button over a communications channel to one or moreof the remaining radios which listen (receive mode) and are oftenreferred to as two-way radios or PTT radios. The AI server 240 whilestill providing all of the ability to vary a verbose response asdescribed by the previous embodiments, further provides additionaladvantages directed to half duplex communication systems.

The communication system 200 may be a broadband system having PTTcapability, such as enabled via broadband-over-PTT server 280. Thecommunication system also may be a narrowband system, such as a publicsafety communications system used by law enforcement, fire rescue, andthe like, comprising the plurality of portable and mobile PTT radios210. The plurality of radios 210 each comprise microprocessor,transceiver and appropriate, RF and controller circuitry for radiocommunication operations.

In accordance with the embodiments, the artificial intelligence (AI)server 240 is incorporated into the communication system 200 forresponding to queries from one or more of the half-duplex radios 210which have been formed into a talkgroup 220. The AI server, aspreviously described is implemented using, a natural language processingsystem and a spoken artificial query response system. Examples of suchprocessing systems include but are not limited to Siri, OK Google, aswell as others known or yet to be developed.

During regular radio operation the talkgroup 220 may be assigned whenany user in the group wishes to converse with another user in thetalkgroup. A vacant radio channel is found automatically by the system200 and the conversation takes place on that channel. Each radiotransceiver, still controlled by its' respective microprocessor, canjoin in the formation of the talkgroup. Thus, formation of the talkgroup220 allows a grouping of radios from within the plurality of radios 210to listen and respond to each other's communications on a separatededicated channel without involving the remaining system of radios.

In accordance with the embodiments, the AI server 240 takes advantage ofthe talkgroup formation to respond to queries from members of thetalkgroup 220. In accordance with the embodiments, the AI serverintelligently interacts with a floor controller 250 to minimizedisruption in communication, maximize channel usage, and prioritizeresponses amongst members of the talkgroup. The incorporation ofartificial intelligence 240 into the communication system 200advantageously allows the half-duplex radios 220 to be operated as inputpoints to receive verbal queries from a member of the talkgroup, therebyconverting the radio device operation into a virtual assistant.

The AI server 240 of the embodiments is able to respond to the querymaking efficient use of channel bandwidth. The application of AI server240 is advantageously applicable to both narrowband and broadbandcommunication systems having push-to-talk (PTT) capability.

In accordance with some embodiments, the AI server 240 intelligentlyinteracts with a floor controller 250, which provides a plurality ofoperational controls to minimize disruption of communication, maximizechannel usage, and prioritize responses amongst members of the talkgroup220. For narrowband devices, such as land mobile radio (LMR) devices,the floor controller 250 may be entirely located within the AI server240, and/or embodied as a standalone floor control server. Forapplications extending the system 200 to broadband devices having PTTcapability, such as certain PTT capable 3/4G LTE and Wi-Fi type devices,the floor controller 250 may be adapted to further operate with and/orbe integrated as part of a push-to-talk on broadband server 280. Serversand networks which support broadband PTT operation may include, but arenot limited to, a WAVE™5000 server by Motorola Solutions, Inc.

In accordance with the following embodiments, system 200 provides the AIserver 240 for time controlled query and response optimization and infurther embodiments an additional query-to-query response feature whichallows for supplemental information to be accessed.

Initially referring to the time controlled query and responseoptimization, in accordance some embodiments the AI server 240intelligently interacts with the floor controller 250 to provideresponses to queries sent out by one or more radios from the one or moretalkgroups, and the timing of responses of at least one of the AIqueries is prioritized based on context information of the communicationsystem.

In accordance with the embodiments, the AI server 240 can be responsiveto predetermined verbal inputs or commands indicative of an AI requestby a talkgroup member to have the AI join the talkgroup. A query sent tothe AI server 240 from a radio in talkgroup 220 can be optimized fortiming and prioritization. For example, a first talkgroup radio 216initiates and sends a verbal request to the floor controller 250 to addartificial intelligence (AI) 240 within the talkgroup 220. The AI server240 joins the talkgroup 220 via 219. By adding the AI into the talkgroup220, the AI 240 and floor controller 250 are able to interoperate withthe radios of the talkgroup 220 to determine response times 262,determine a request or assign priority 264, adjust different floorcontrols 266, determine delays in delivery, delays based on confidencelevels, and all other control functions related to timing andprioritization that can further enhance the management of the queryresponse system.

In accordance with a further query embodiment, talkgroup assignment canalso be modified into sub talkgroups based on the query sent from theoriginating radio. For example, in response to a radio 218 sending aquery to which the response is only to be played to two designatedradios, 216 and 218, the AI server 240 responds by assigning theresponse to sub-talkgroup (SUB-T/G) 222, so that the response is onlyheard by members 216, 218 of the sub-talkgroup 222.

Accordingly, the system 200 allows for specifying, to the AI server 240,by the radio sending the query, such as radio 216, a subgroup 222 oftalkgroup members 216, 218 from talkgroup 220, to hear the response, andsending the response, by the AI server, to the subgroup 222 of talkgroupmembers.

The AI server 240 responds to other queries from members of thetalkgroup 220 within the radio communication system 200. The AI serverintelligently interacts with a floor controller 240 to minimizedisruption in communication, maximize channel usage, and prioritizeresponses amongst members of the talkgroup. The incorporation ofartificial intelligence into a public safety radio communication systemadvantageously provides half-duplex radios with additional verbal and/ortext query and response while maintaining regular talkgroup operation.The application of AI is applicable to both narrowband and broadbandcommunication systems having push-to-talk (PTT) capability.

Additionally, in a public safety environment, it is important that theAI server 240 provide useful information in response to user queries soas not to inhibit time-critical public safety services (e.g., respondingto a distress call, responding to an emergency at a correct location,and the like). Therefore, in some embodiments it may be advantageous tohave the AI server 240 alternatively be automatically assigned to everytalkgroup upon formation of such Talkgroups within the communicationsystem 200.

In some embodiments, the AI server 240 may insert itself into thetalkgroup based on certain keyword triggers. This self-insertion requestis particularly advantageous for announcements, events, and the like.For example, if a user of a portable device asks to another member ofthe talkgroup “When does Main Street close for the holiday parade?” ifno response is provided within a certain amount of time by a member ofthe Talkgroup, then the AI server will self insert into the talkgroupand respond to the query. For example, “Main Street will close between10 am and noon for the holiday parade.” Additional information may evenfurther advantageously be provided by the AI server 240, of which anindividual user might not be aware, such as: “Detour provided at SecondStreet.”

In accordance with further embodiments, if the AI server 240 is unableto determine a response to a search query after a predetermined time,the AI server can automatically remove itself from the talkgroup, andeven redirect the query to another source, if available, such as thedispatcher 230, multi media 270 or another talkgroup member. Themultimedia resource 270 may provide, for example, a streaming videoresponse in response to a redirected query. The dispatcher 240 may be anarrowband dispatcher or a broadband dispatcher. This self-removal ofthe AI advantageously maintains efficiency of the system 200 byredirecting queries 249, 269 to other resources, freeing up the AIserver to attend to other queries to which it can provide a response.

For embodiments in which the AI 240 redirects the query to anotherresource to obtain supplemental information, these queries may beredirected, for example, to dispatcher 230 in text format inquiring ifthe dispatcher has resources to answer the query. The decision to sendthe query to the dispatcher 230 may be based on contexts factorsassociated with that dispatcher and knowledge of the working environmentof the various radio users of the plurality of radios 210, and assignedmembers working in talkgroups within the communication system 200. Floorcontrol is automatically provided to dispatcher 230 upon confirmationthat the dispatcher 230 does indeed have information with which torespond to the query. The dispatcher 230 then sends a verbal responseover dispatch radio to the query radio of the talkgroup 220.

In other embodiments to obtain supplemental information, the AI 240 mayverbally inquire to other radios of the talkgroup 220 as to whether theyhave information with which to respond to the query. If a radio memberconfirms such knowledge, then the AI server 240 can redirect the queryto that radio member within the talkgroup 220 along with providing floorcontrol to respond to the query. A response can then be played out fromthe initiating radio. Depending on the type of query sent, the responsemay be played out to all or some members of a talkgroup. If the queryincluded a command or instruction to restrict the response to certaintalkgroup members (radios 216, 218 of the sub-group 222), then theresponse can be limited to those members as previously described. Thus,although it may be important for a response to get to one or moremembers, and that the group be aware of that situation, it may not benecessary for the entire talkgroup to listen to the response. It can besufficient for certain members to simply be made aware that a responsedid occur.

In another supplemental information embodiment, the redirected query maybe a text query sent to the multimedia resource 270 which may, as aresult of the query, generate a streaming video response fortransmission back to the initiating query radio 216. The streaming videomay be played out at all radios of sub-talkgroup 222, which in thisexample is formed of radios 216 and 218. If no sub-talkgroup was formed,and no other restrictions were placed, the streaming video can be playedout through the radios members of talkgroup 220.

In another supplemental information embodiment, the redirected query maybe a text query sent to the dispatcher 230 operating in broadband. Thedispatcher 230 can generate a video streaming response for transmissionback to the initiating query radio 216. Hence, a video streamingresponse to a verbal query that originally initiated at a half duplexradio 216 has been provided, by using the AI server's ability toredirect queries.

In accordance with further embodiments, the control of the timing andthe control of the supplemental information are optimized throughvarious floor control operations of communication system 200. Floorcontroller 250 of AI server 230 provides floor control operations basedon a variety of floor control factors 260, of which only a few areshown. Floor control operations may be based on the length of anexpected response. For example, the AI server 240 can request and/orlock the floor for a predetermined required time to complete a response262.

Priority of an AI floor request can be dependent on a radio requestorpriority. Some radio users, identified by radio user ID, and/or sometypes of verbal requests may have a higher priority and be responded toprior to others 264.

If a channel is heavily used, the AI server 240 can adjust contentand/or depth of a response to fill available floor time 266. Forexample, a radio channel which is heavily used may have a responseadjusted into a summary response so as not to impact channel usage.

In some embodiments, it may be desirable to have an order of responsecontent prioritized and segmented into smaller responses, therebyfreeing up channel availability between responses.

Priority (and thus capability to interrupt AI) of other talkgroupmembers can be adjusted based on the applicability of the content tothem. For instance, if a member of the talkgroup is listening to aresponse and determines that the response is no longer relevant to thetalkgroups current conditions or needs further detail, that higherpriority user can interrupt the response by pressing PTT and verbalizinga new query. For example, if rookie police office sent a query askingfor an entire map to be streamed 219 over multimedia 270 of the entireholiday parade route, then a senior office could interrupt that responsewith a query “does the holiday parade cross Main and Second Street?”

Accordingly, by incorporating floor control operations with artificialintelligence, communication systems, such as a public safetycommunication system, and half duplex radios operating within the systemcan now advantageously provide talkgroup operation with additional querysearch capability.

FIG. 3 shows an example of a communication exchange diagram in whichartificial intelligence is added as a member of the talkgroup inaccordance with some of the embodiments. At 310, a first sub-talkgroupradio 301 sends a verbal request to add artificial intelligence (AI)within the talkgroup. This request is received by group manager 350(equivalent to floor controller of FIG. 2) at 310. The request 310triggers a response from the group manager 350 to add artificialintelligence 340 (AI) to the talkgroup at 312. By adding the artificialintelligence 340 into the group, the AI 340 and floor manager 350 areable to interoperate with the radios of the talkgroup to determineresponse times, an increase or decrease in delivery time, determinepriority, assign priority, and all other control functions that canfurther enhance the management of the query response system.

A query is sent at 314 to the AI 340 from a second sub-talkgroup radio304. A word analysis is performed by the AI 340 to determine aconfidence level that the query is intended for the AI. Depending on theconfidence level, a request for a delay is sent to the floor 350, asindicated at 316 where the AI 340 sends a request to the group manager350 requesting floor time at a particular time, T, and for apredetermined duration time, Td. The group manager 350 then proceeds togrant the floor to the AI 340 at 318. The AI 340 has already completedthe search and is ready to generate and send a response to radios 302and 301 at 320, after which time the floor can be removed at 322.

The response from the AI is sent to the query radio 302, andautomatically also sent to the initiator radio 301, unless otherwisespecified by the requestor. These radios are all operating on the samesub-talkgroup channel, so unless there is an instruction to assign ordirect the response to a different free channel, then all the radioswithin the talkgroup will hear the response.

Thus, the timeline 300 illustrates has demonstrated some of the timingfactors that can be taken into consideration in accordance with theembodiments.

Referring to FIG. 4, there is shown a method 400 in accordance with aquery-to-query embodiment. The query-to-query embodiment allows forsupplemental information to be acquired beyond that normally availablefrom the AI server 240 of FIG. 2. Beginning at 402 a talkgroup is formedfrom a plurality of radios followed by initiating a query at one of theradios via the push-to-talk (PTT) button at 404.

The method can further comprise triggering the AI server via an input ofthe radio prior to initiating the query, thereby allowing the AI serverto join the talkgroup. The input to the radio (the trigger) can be forexample, a PTT verbal pre-command, and/or a non-PTT out of band textmessage, depending on the type of system. The search query can followthe pre-command. For example, the pre-command may be the spoken word“Einstein”, followed by the search query “How many registered firearmsare located at this location?”

The method 400 proceeds by transmitting the search query at 406 to theAI artificial intelligence server, the AI server being the AI server 240of FIG. 2 having natural language processing and response capability aspreviously described.

At 408, in accordance with the query-to-query embodiment, in response toreceiving the query, the AI server determines that an alternate responseresource is capable of responding to the query or providing a betterresponse. The AI server 240 then requests that the floor controller 250give the talkgroup floor to the alternate response resource at 410, suchas dispatcher 230 or another radio of the talkgroup of FIG. 2. Theverbal query is redirected from the AI server 240 via the floorcontroller to alternate resource at 412. In some embodiments it may beuseful for the AI server to convert the verbal query to a text queryprior to redirecting the query to the alternate resource. For example,verbal queries converted to text format can be redirected to thedispatcher 230 from the AI server 240. Text format is preferred so asnot to disrupt dispatch radio audio communications which may be on-goingwith other users. An advantage of redirecting a query request to adispatcher 230 is that this dispatch resource can research the textversion of the query and return, via dispatch transmit, a verbalresearched response to the initiating query radio. The response is thusprovided straight from the dispatcher 230 to the initiating query radio216 without having to go back through the AI server 240, furtherenhancing efficiency of operation.

If the AI server does not know the answer to a query or determines thatan alternate source would have a better response, the AI server can alsoredirect the query to that source. For example another member of thetalkgroup or a multimedia source 270.

The floor controller 250 automatically provides the floor to thealternative resource when the AI server 240 seeks additional informationto the query or redirects the query. Utilizing alternate resourcesfurther provides improved use of channel bandwidth and efficiency inmanaging the query response portion of the communication system.

Moving to FIG. 5, a method 500 is shown which summarizes the timingembodiments that have been described in FIG. 2. Method 500 begins withthe formation of a talkgroup at 502, followed by sending a query from aPTT radio device at 504. In some embodiments, AI server mayautomatically insert and later remove itself from the talkgroup uponsending the response. In some embodiments, the AI server 240 and a floorcontroller 250 may automatically be assigned upon formation of one ormore talkgroups within a communication system. In yet still otherembodiments, a radio member of the talkgroup sends an AI request, as wasdescribed in FIG. 3, for the AI server to join the talkgroup.

In accordance with some embodiments, controlling timing andprioritization of the response sent to the PTT device by the AI serverwill greatly improve the overall management of the query responsesystem. For example, the AI server 240 of FIG. 2 waiting to generate andsend the response, until after a predetermined response wait time hasexpired, provides members of the talkgroup the opportunity to providerelevant information and make other members aware of it. Using theexpiration wait time provides the assurance that a response to thequery, from the AI server, can still be received when no member of thetalkgroup is able to respond. The wait time can be determined based onanalyzing the query to provide a confidence level that the query wasintended for the AI 240, radio channel bandwidth and the AI server'sfloor control availability, or any combination of, thereby providingefficient control of channel usage. Analyzing the query to determine theconfidence level may include name searching. For example, if the AI isnamed Einstein, and the query includes the name “Einstein” theconfidence will be very high that this is a query directed to the AI240. When the confidence is high, the AI 240 can respond immediately andhence have a zero wait time. However, if the query starts with the nameof another user in the talkgroup, it is likely that the query was notdirected to the AI server. In this case, the AI waits the maximum waittime before responding. If during the wait time, the AI determines thatthe requestee has responded, then the AI 240 will not respond unless ithas additional information that would be useful.

The method 500 can be further enhanced if desired by applying priority.For example, by determining a priority for sending a response from theAI server 240, and sending the response based on the priority.Prioritizing of a radio query, and its' subsequent response, may bebased on context factors, such as radio user identity, rank ofrequestor, rank of other members of the talkgroup, number of members inthe talkgroup. For example, a Fire Chief, a Police Officer, a Detective,to name a few. Prioritizing of the radio query may also be based oncontext factors associated with an incident scene of the query radio,such as incident scene type and public safety information pertaining tothe incident scene. For example, traffic accident, airplane explosion,train derailment, robbery, home invasion, are just a few examples. Theprioritizing of the radio query may be based on verbal query wordshaving predetermined keyword priority rankings, such as “FIRE”, “TOXIC”,“EMERGENCY”, “POISON” and “EXPLOSION” and the like.

In accordance with some embodiments method 500 may further adjust aresponse wait time, by the AI server based on a confidence level thatthe verbal query was intended for the AI server or for members of thetalkgroup.

In accordance with some embodiments method 500 may further determine ananticipated response time. Depending on the type of priority, it mayfurther be desired to lock the floor control for the anticipatedresponse time. For example, in mission critical events, such as firerescue, the generation and transmission of a high priority response iscritical when other members of a talkgroup have not been able to answera query and the confidence level is fairly high that the intendedrecipient of the query is now the AI server 240.

Method 500 can be further enhanced by re-prioritizing automated verbalresponses to the query, from the AI server 240, in response to changesin incident scene context determined by the AI server, wherein theincident scene context is monitored as part of the query.

The following Table provides a few examples Confidence levels, ChannelOccupancy, AI priority, wait time, and response time needed.

Conf. Level Required Effect that Response Timeline/ Query is CH AILength Verbosity/ Req. for AI AVL Priority Wait Time Query-to-Query TypeQuery (H/M/L) (H/M/L) (H/M/L) Time (seconds) Information Fire Einstein,H L H 0 30 Timeline Chief What AI requests CH. availability flammablefor 30 seconds with high materials are priority to send response in this“Chemicals, x, y, z” building? Police Who are M L M 10 10 TimelineOfficer members AI waits 10 seconds to see if ABC Gang? anyone responds,if not, then requests floor for 5 seconds to send response “member namesLee, Barb” Detective What plate L L M 10 10 Query-Query info. & numberson Timeline red corvette? AI does not have answer, but determines thatOfficer Smith should know answer, AI waits for officer to answer, if noresponse then requests floor. “Officer Smith, please provide licenseplate #s from your position.” AI transfers floor control to OfficerSmith

The Table is meant to provide non-limiting, examples of just a fewscenarios in which the various embodiments be applied.

Accordingly, there has been provided a communication systemincorporating artificial intelligence and methods for controlling an AIserver within the system. A method for varying verbosity of response, amethod for determining timing of a response, and a method for obtainingsupplemental information for a response have all been provided. Thesystem and methods have provided for optimized usage of channelbandwidth, improved timing, and redirection of query/response for moreaccurate information acquisition. Improved management of virtualassistant search queries and responses can now be obtained using anartificial intelligence (AI) server managed in accordance with thedescribed methods provided by the various embodiments.

In the foregoing specification, specific embodiments have beendescribed. However, one of ordinary skill in the art appreciates thatvarious modifications and changes can be made without departing from thescope of the invention as set forth in the claims below. Accordingly,the specification and figures are to be regarded in an illustrativerather than a restrictive sense, and all such modifications are intendedto be included within the scope of present teachings.

The benefits, advantages, solutions to problems, and any element(s) thatmay cause any benefit, advantage, or solution to occur or become morepronounced are not to be construed as a critical, required, or essentialfeatures or elements of any or all the claims. The invention is definedsolely by the appended claims including any amendments made during thependency of this application and all equivalents of those claims asissued.

Moreover in this document, relational terms such as first and second,top and bottom, and the like may be used solely to distinguish oneentity or action from another entity or action without necessarilyrequiring or implying any actual such relationship or order between suchentities or actions. The terms “comprises,” “comprising,” “has”,“having,” “includes”, “including,” “contains”, “containing” or any othervariation thereof, are intended to cover a non-exclusive inclusion, suchthat a process, method, article, or apparatus that comprises, has,includes, contains a list of elements does not include only thoseelements but may include other elements not expressly listed or inherentto such process, method, article, or apparatus. An element proceeded by“comprises . . . a”, “has . . . a”, “includes . . . a”, “contains . . .a” does not, without more constraints, preclude the existence ofadditional identical elements in the process, method, article, orapparatus that comprises, has, includes, contains the element. The terms“a” and “an” are defined as one or more unless explicitly statedotherwise herein. The terms “substantially”, “essentially”,“approximately”, “about” or any other version thereof, are defined asbeing close to as understood by one of ordinary skill in the art, and inone non-limiting embodiment the term is defined to be within 10%, inanother embodiment within 5%, in another embodiment within 1% and inanother embodiment within 0.5%. The term “coupled” as used herein isdefined as connected, although not necessarily directly and notnecessarily mechanically. A device or structure that is “configured” ina certain way is configured in at least that way, but may also beconfigured in ways that are not listed.

It will be appreciated that some embodiments may be comprised of one ormore generic or specialized processors (or “processing devices”) such asmicroprocessors, digital signal processors, customized processors andfield programmable gate arrays (FPGAs) and unique stored programinstructions (including both software and firmware) that control the oneor more processors to implement, in conjunction with certainnon-processor circuits, some, most, or all of the functions of themethod and/or apparatus described herein. Alternatively, some or allfunctions could be implemented by a state machine that has no storedprogram instructions, or in one or more application specific integratedcircuits (ASICs), in which each function or some combinations of certainof the functions are implemented as custom logic. Of course, acombination of the two approaches could be used.

Moreover, an embodiment can be implemented as a computer-readablestorage medium having computer readable code stored thereon forprogramming a computer (e.g., comprising a processor) to perform amethod as described and claimed herein. Examples of suchcomputer-readable storage mediums include, but are not limited to, ahard disk, a CD-ROM, an optical storage device, a magnetic storagedevice, a ROM (Read Only Memory), a PROM (Programmable Read OnlyMemory), an EPROM (Erasable Programmable Read Only Memory), an EEPROM(Electrically Erasable Programmable Read Only Memory) and a Flashmemory. Further, it is expected that one of ordinary skill,notwithstanding possibly significant effort and many design choicesmotivated by, for example, available time, current technology, andeconomic considerations, when guided by the concepts and principlesdisclosed herein will be readily capable of generating such softwareinstructions and programs and ICs with minimal experimentation.

The Abstract of the Disclosure is provided to allow the reader toquickly ascertain the nature of the technical disclosure. It issubmitted with the understanding that it will not be used to interpretor limit the scope or meaning of the claims. In addition, in theforegoing Detailed Description, it can be seen that various features aregrouped together in various embodiments for the purpose of streamliningthe disclosure. This method of disclosure is not to be interpreted asreflecting an intention that the claimed embodiments require morefeatures than are expressly recited in each claim. Rather, as thefollowing claims reflect, inventive subject matter lies in less than allfeatures of a single disclosed embodiment. Thus the following claims arehereby incorporated into the Detailed Description, with each claimstanding on its own as a separately claimed subject matter.

I claim:
 1. A method of receiving information, comprising: forming atalkgroup from a plurality of radios; sending a verbal query via a(push-to-talk) PTT radio of the talkgroup to at least one of the membersof the talkgroup; generating and sending a verbal response to the verbalquery from an AI server, the AI server having natural languageprocessing and response capability, after a predetermined verbalresponse wait time from the talkgroup has expired with no verbalresponse being generated by the talkgroup; and prioritizing automatedresponses to the verbal query in response to changes in incident scenecontext information determined by the AI server.
 2. The method of claim1, further comprising: receiving a response to the verbal query fromanother radio of the talkgroup prior to the wait time expiring.
 3. Themethod of claim 1, further comprising: receiving a response to theverbal query from the AI server after the predetermined wait time hasexpired.
 4. The method of claim 1, wherein the wait time is determinedbased on radio channel bandwidth and the AI server's floor controlavailability.
 5. The method of claim 1 further comprising; determining apriority for sending a verbal response from the AI server; and sendingthe response based on the priority.
 6. The method of claim 1, furthercomprising: prioritizing the radio verbal query, by the AI server or afloor controller, based on context factors.
 7. The method of claim 6,wherein the context factors are associated with the talkgroup andcomprise one or more of: radio user identity, rank of requestor, rank ofother members of the talkgroup, number of members in the talkgroup. 8.The method of claim 6, wherein the context factors are associated withan incident scene of the query radio and comprises: incident scene typeand public safety information pertaining to the incident scene.
 9. Themethod of claim 1, further comprising: automatically assigning the AIserver and a floor controller upon formation of one or more talkgroupswithin a communication system.
 10. The method of claim 1, furthercomprising; adjusting a response wait time, by the AI server based on aconfidence level that the verbal query was intended for the AI server orfor members of the talkgroup.
 11. The method of claim 1, furthercomprising: determining an anticipated response time; and locking afloor control, by the AI server, for the anticipated response time. 12.The method of claim 1, further comprising: specifying, to the AI server,by the radio sending the query, a subgroup of talkgroup members to hearthe response; and sending the response, by the AI server, to thesubgroup of talkgroup members.
 13. The method of claim 1, furthercomprising: wherein the AI server automatically removes itself from thetalkgroup upon sending the response.
 14. The method of claim 1, whereinthe AI server provides additional information to the verbal query aftera verbal response has been generated by the talkgroup.
 15. The method ofclaim 1, wherein the AI server, without being queried, automaticallyinserts itself into the talkgroup and sends a response to a query radioof the talkgroup.
 16. The method of claim 1, wherein the AI server isautomatically assigned upon formation of one or more talkgroups withinthe communication system.
 17. The method of claim 1, wherein a radiomember of the talkgroup sends an AI request for the AI server to jointhe talkgroup.
 18. A method of receiving information, comprising:forming a talkgroup from a plurality of radios; sending a verbal queryvia a (push-to-talk) PTT radio of the talkgroup to at least one of themembers of the talkgroup; generating and sending a verbal response tothe verbal query from an AI server, the AI server having naturallanguage processing and response capability, after a predeterminedverbal response wait time from the talkgroup has expired with no verbalresponse being generated by the talkgroup; prioritizing a radio querybased on verbal query words having predetermined keyword priorityrankings; and re-prioritizing automated verbal responses to the query,from the AI server, in response to changes in incident scene contextdetermined by the AI server, wherein the incident scene context ismonitored as part of the query.
 19. A communication system, comprising:a plurality of radios having half-duplex functionality, the plurality ofradios forming one or more talkgroups; an artificial intelligence (AI)server providing a natural language processing query and responsedatabase; a floor controller for scheduling query and responseoperation; the AI server intelligently interacting with the floorcontroller to provide responses to verbal queries sent out by one ormore radios from the one or more talkgroups; timing of verbal responsesof at least one of the AI verbal queries being prioritized based oncontext information of the communication system; and wherein the AIserver prioritizes automated responses to the verbal query in responseto changes in incident scene context information determined by the AIserver.
 20. The communication system 19, wherein the talkgroup compriseshalf-duplex radios operating in a narrowband network.
 21. Thecommunication system 19, wherein the talkgroup comprises half-duplexradios operating in a broadband network.
 22. The communication system19, wherein the talkgroup is a public safety communications talkgroupand the AI server and the floor controller prioritize timing ofresponses to queries based on context information within the publicsafety communication system.
 23. The communication system of claim 19,wherein the AI server provides additional information to the verbalquery after a verbal response has been generated by the talkgroup. 24.The communication system 19, wherein the AI server, without beingqueried, automatically inserts itself into the talkgroup and sends aresponse to a query radio of the talkgroup.
 25. The communication system19, wherein the AI server is automatically assigned upon formation ofone or more talkgroups within the communication system.
 26. Thecommunication system 19, wherein a radio member of the talkgroup sendsan AI request for the AI server to join the talkgroup.
 27. Thecommunication system 19, wherein the timing for the AI server to respondis further based on a predetermined response wait time within which noverbal response is generated by the one or more talkgroups.
 28. Acommunication system, comprising, a push-to-talk (PTT) communicationdevice having talkgroup capability; an artificial intelligence (AI)server having language processing and response capability; and a floorcontroller for interoperatively controlling timing and prioritization ofverbal query and verbal response between the PTT communication deviceand the AI server, wherein the AI server prioritizes automated responsesto the verbal query in response to changes in incident scene contextinformation determined by the AI server.
 29. The communication system ofclaim 28, wherein the talkgroup comprises half-duplex radios operatingin a narrowband network.
 30. The communication system 28, wherein thetalkgroup comprises half-duplex radios operating in a broadband network.31. The communication system 28, comprising, wherein the AI server,without being queried, automatically inserts itself into the talkgroupand sends a response to a query radio of the talkgroup.
 32. Thecommunication system of claim 28, wherein the AI server providesadditional information to the verbal query after a verbal response hasbeen generated by a talkgroup.
 33. The communication system 28, whereinthe AI server is automatically assigned upon formation of one or moretalkgroups within the communication system.
 34. The communication system28, wherein a radio member of the talkgroup sends an AI request for theAI server to join the talkgroup.
 35. The communication system 28,wherein the AI server responds to the verbal query after a predeterminedverbal response wait time within which a talkgroup has not responded tothe verbal query.
 36. A method of receiving information, comprising:forming a talkgroup from a plurality of radios; sending a verbal queryvia a (push-to-talk) PTT radio of the talkgroup to at least one of themembers of the talkgroup; generating and sending a verbal response tothe verbal query from an AI server, the AI server having naturallanguage processing and response capability, after a predeterminedverbal response wait time from the talkgroup has expired with no verbalresponse being generated by the talkgroup; determining an anticipatedresponse time; and locking the floor control, by the AI server, for theanticipated response time.
 37. A method of receiving information,comprising: forming a talkgroup from a plurality of radios; sending averbal query via a (push-to-talk) PTT radio of the talkgroup to at leastone of the members of the talkgroup; generating and sending a verbalresponse to the verbal query from an AI server, the AI server havingnatural language processing and response capability, after apredetermined verbal response wait time from the talkgroup has expiredwith no verbal response being generated by the talkgroup, wherein the AIserver provides additional information to the verbal query after averbal response has been generated by the talkgroup.
 38. A communicationsystem, comprising: a plurality of radios having half-duplexfunctionality, the plurality of radios forming one or more talkgroups;an artificial intelligence (AI) server providing a natural languageprocessing query and response database; a floor controller forscheduling query and response operation; the AI server intelligentlyinteracting with the floor controller to provide responses to verbalqueries sent out by one or more radios from the one or more talkgroups;and timing of verbal responses of at least one of the AI verbal queriesbeing prioritized based on context information of the communicationsystem, wherein the AI server provides additional information to theverbal query after a verbal response has been generated by thetalkgroup.
 39. A communication system, comprising, a push-to-talk (PTT)communication device having talkgroup capability; an artificialintelligence (AI) server having language processing and responsecapability; and a floor controller for interoperatively controllingtiming and prioritization of verbal query and verbal response betweenthe PTT communication device and the AI server, wherein the AI serverprovides additional information to the verbal query after a verbalresponse has been generated by a talkgroup.